1. Field of the Invention
The present invention relates generally to the field of downhole sampling of hydrocarbons and in particular to downhole and onsite surface high resolution spectroscopy of hydrocarbon samples using a tunable optical filter for measurement and estimation of physical and chemical properties of fluid from a downhole formation.
2. Background Information
In the oil and gas industry, formation testing tools have been used for monitoring formation pressures along a wellbore, obtaining formation fluid samples from the wellbore and predicting performance of reservoirs around the wellbore. Such formation testing tools typically contain an elongated body having an elastomeric packer that is sealingly urged against the zone of interest in the wellbore to collect formation fluid samples in storage chambers placed in the tool.
During drilling of a wellbore, a drilling fluid (“mud”) is used to facilitate the drilling process and to maintain a pressure in the wellbore greater than the fluid pressure in the formations surrounding the wellbore. This is particularly important when drilling into formations where the pressure is abnormally high. If the fluid pressure in the borehole drops below the formation pressure, there is a risk of blowout of the well. As a result of this pressure difference, the drilling fluid penetrates into or invades the formations for varying radial depths (referred to generally as invaded zones) depending upon the types of formation and drilling fluid used. The formation testing tools retrieve formation fluids from the desired formations or zones of interest, test the retrieved fluids to ensure that the retrieved fluid is substantially free of mud filtrates, and collect such fluids in one or more chambers associated with the tool. The collected fluids are brought to the surface and analyzed to determine properties of such fluids and to determine the condition of the zones or formations from where such fluids have been collected.
One feature that most formation testing tools have in common is a fluid sampling probe. This may consist of a durable rubber pad that is mechanically pressed against the rock formation adjacent the borehole, the pad being pressed hard enough to form a hydraulic seal. Through the pad is extended one end of a metal tube that also makes contact with the formation. This tube (“probe”) is connected to a sample chamber that, in turn, is connected to a pump that operates to lower the pressure at the attached probe. When the pressure in the probe is lowered below the pressure of the formation fluids, the formation fluids are drawn through the probe into the well bore to flush the invaded fluids prior to sampling. In some formation tests, a fluid identification sensor determines when the fluid from the probe consists substantially of formation fluids; then a system of valves, tubes, sample chambers, and pumps makes it possible to recover one or more fluid samples that can be retrieved and analyzed when the sampling device is recovered from the borehole.
It is desirable that only uncontaminated fluids are collected, in the same condition in which they exist in the formations. Commonly, the retrieved fluids are contaminated by drilling fluids. This may happen as a result of a poor seal between the sampling pad and the borehole wall, allowing borehole fluid to seep into the probe. The mud cake formed by the drilling fluids may allow some mud filtrate to continue to invade and seep around the pad. Even when there is an effective seal, borehole fluid (or some components of the borehole fluid) may “invade” the formation, particularly if it is a porous formation, and be drawn into the sampling probe along with connate formation fluids.
U.S. Pat. No. 4,994,671 issued to Safinya et al. discloses a device in which visible and near infrared (IR) analysis of the fluids is done in the borehole, primarily for the purpose of determining when a fluid being pumped has reached its minimum filtrate contamination and is worth collecting into a sample tank, which will be subsequently be brought back to the surface. The infrared portion part of the electromagnetic spectrum (0.8 to 25 μm wavelength region, or equivalently wavenumbers of 12,500 to 400 cm−1) of a substance contains absorption features due to the molecular vibrations or rotations of the constituent molecules. The absorptions arise from both fundamentals (single quantum transitions occurring in the mid-infrared region from 2.5-25.0 microns) and combination bands and overtones (multiple quanta transitions occurring in the mid- and the near-infrared region from 0.8-2.5 microns). The position (frequency or wavelength) of these absorptions contain information as to the types of molecular structures that are present in the material, and the intensity of the absorptions contains information about the amounts of the molecular types that are present. To use the information in the spectra for the purpose of identifying and quantifying either components or properties requires that a calibration be performed to establish the relationship between the absorbances and the component or property that is to be estimated. For complex mixtures, where considerable overlap between the absorptions of individual constituents occurs, such calibrations must be accomplished using various chemometric data analysis methods.
In complex mixtures, each constituent in the retrieved fluid generally gives rise to multiple absorption features corresponding to different vibrational motions. To first order, the effect on the mixture spectra of any interactions (e.g., hydrogen bonding) between the molecules of different components are negligible so that Beer's Law is obeyed and the intensities of these absorptions will all vary together in a linear fashion as the concentration of the constituent varies. Such features are said to have intensities which are correlated in the frequency (or wavelength) domain. This correlation allows these absorptions to be mathematically distinguished from unrelated spectral features and from random spectral measurement noise which shows no such correlation. The linear algebra computations which separate the correlated absorbance signals from the uncorrelated ones form the basis for techniques such as Multiple Linear Regression (MLR), Principal Components Regression (PCR) and Partial Least Squares (PLS). As is well known, PCR is essentially the analytical mathematical procedure of Principal Components Analysis (PCA) followed by regression analysis.
PCR and PLS have been used to estimate elemental and chemical compositions and to a lesser extent physical or thermodynamic properties of solids, liquids and gases based on their mid- or near-infrared spectra. Some examples of using chemometrics to infer physical and chemical properties of crude oils from their near-infrared spectra were given in 1988 in GB 2,217,838A where the spectra were obtained in the laboratory using a high-resolution (2-nm step size) spectrometer. Typically, chemometric methods involve: [1] the collection of mid-infrared or near-infrared spectra of a set of representative samples; [2] mathematical treatment of the spectral data to extract the best correlating individual wavelengths (MLR), or Principal Components or Partial Least Squares latent variables (e.g. the correlated absorbance signals described above); and [39 regression of these spectral variables against composition and/or property data to build a multivariate model. The analysis of new samples then involves the collection of their spectra, the decomposition of the spectra in terms of the spectral variables used in the regression and the application of the regression equation to calculate the composition or properties.
In Safinya et al., visible and near-infrared light is passed through the fluid sample. Then, a spectrometer (which is actually a filter photometer that has 10 filters at different center wavelengths) measures the spectrum of the transmitted and the back scattered light, and, knowing the spectrum of the incident light, transmission and backscattered absorption spectra for the sample are determined. Using absorption spectra of water, and particular examples of absorption spectra of gas, crude and refined oils, and drilling fluids, a least squares analysis is performed that models the observed spectra as a weighted sum of the spectra of its components, the least squares analysis giving the composition of the fluid in terms of weights of the various components. The Safinya method assumes that the spectra of the crude oil and of the filtrate that comprise a contaminated formation fluid mixture are the same as whatever example crude oil and filtrate spectra were chosen for the least-squares fitting. However, when testing any hydrocarbon-bearing zone for the first time, that assumption is problematic because of the high variability of crude oil spectra.
Currently, typical downhole spectrometers are actually filter photometers. They use fixed, single-color interference filters whose bandpass resolution is limited to no better than 11 nm full width at half maximum because of the present state of the art for manufacturing interference-filters, thus providing relatively low spectroscopic resolution at a small number of selected center wavelengths (e.g., 10 to 24 different optical filters). These filters are not suitable to distinguish between closely spaced spectral peaks or to identity isotopes whose spectral peak spacings are much smaller than 11 nm. Thus, there is a need for an analysis technique suitable for downhole and onsite surface spectroscopic analysis of hydrocarbon samples with higher resolution.